1. Field
Invention relates to detection of semiconductor fabrication defects, and in particular to a method and system for predictive, automatic and self-learning semiconductor fabrication defect signature recognition and defect sourcing.
2. Related Art
Conventional semiconductor fabrication systems incorporate statistical process control and impose control limits on the acceptable number of defects on a wafer, detect quantity of defects on a given wafer, and raise a flag if the quantity falls out of bounds. Defective wafers are inspected by human experts in the hope of pinpointing the fabrication process steps responsible for the defect. Drawbacks of this approach include: (a) defect signature recognition is primitive, and flags are raised too late and after yields have already dropped; (b) identification of the defect source is done by humans and represents a tedious and time consuming effort; and (c) successful defect sourcing depends on expert know-how that is difficult to capture.
Accordingly, there is need for (a) predictive, (b) automatic and (c) self-learning semiconductor fabrication defect signature recognition and sourcing for addressing the above problems.